• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.85-94
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• 2009

In this work we propose an energy-efficient transmission strategy for wireless sensor networks that operate in a strict energy-constrained environment. Our transmission algorithm consists of two components: a binary-decision based transmission and a channel-aware backoff adjustment. In the binary-decision based transmission, we obtain the optimum threshold for successful transmission via Markov decision process (MDP) formulation. A channel-aware backoff adjustment, the second component of our proposal, is introduced to favor sensor nodes seeing better channel in terms of transmission priority. Extensive simulations are performed to verify the performance of our proposal over fading wireless channels.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.577-579
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• 1992

A new algorithm, which combines the Evolution Strategy and the Simplex method, is proposed for the detection of magnetic body utilizing the disturbance of magnetic fields. Although the detection problem of magnetic body which belongs to the inverse problem may have many local minima, the global optimum point was found by introducing the Evolution Strategy. And the convergency rate was enhanced by introducing the Simplex method. Through the numerical examples, the applicability and usefulness of the proposed algorithm are proved.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.144-147
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• 2006

A proportional intergral (PI) control strategy is commonly used for constant current and extinction angle control in a HVDC (High Voltage Direct Current) system. A PI control strategy is based on a stactic design where the gains of a PI controller are fixed. Since the response of a HVDC plant dynamically changes with variations in the operation point a PI controller performance is far from optimum. The contribution of this paper is the presentation of the design of a rough set based, fuzzy adaptive control scheme. Experimental results that compare the performance of the adaptive control and PI control schemes are also given.

• Structural Engineering and Mechanics
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• v.29 no.6
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• pp.603-622
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• 2008

This work deals with the design optimization of tuned mass damper (TMD) devices used for mitigating vibrations in high-rise towers subjected to seismic accelerations. A stochastic approach is developed and the excitation is represented by a stationary filtered stochastic process. The effectiveness of the vibration control strategy is evaluated by expressing the objective function as the reduction factor of the structural response in terms of displacement and absolute acceleration. The mechanical characteristics of the tuned mass damper represent the design variables. Analyses of sensitivities are carried out by varying the input and structural parameters in order to assess the efficiency of the TMD strategy. Variations between two different criteria are also evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.268-275
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• 2000

The increasing technological demands of today call for complex systems, which in turn involve a series of optimization problems with some equality or inequality constraints. In this paper, we presents a real-coded genetic algorithm(RCGA) as an optimization tool which is implemented by three genetic operators based on real coding representation. Through a lot of simulation works, the optimum settings of its control parameters are obtained on the basis of global off-line robustness for use in off-line applications. Two optimization problems are Presented to illustrate the usefulness of the RCGA. In case of a constrained problem, a penalty strategy is incorporated to transform the constrained problem into an unconstrained problem by penalizing infeasible solutions.

• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.627-639
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• 2002

Bridge construction is almost complete in many countries. Thus, the government and highway agencies change their focus from constructing to maintaining. Effectively maintaining bridges require predicting their lifespan using a system reliability viewpoint. Likewise, maintenance models based on the system reliability concept should be developed. Thus, this study developed maintenance models for preventive maintenance and essential maintenance using system reliability and lifetime distributions. The optimal maintenance strategy for an existing bridge was obtained using the developed maintenance models.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.283-289
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• 2004

Rail defects(Corrugation, shelling, etc) are occurred by the Rail with wheel contact stress. Rail grinding is maintaining of optimal rail profile to use special rail grinding machine to remove rail defect. The benefits of rail grinding enforcement, improve track safety, improve track steering and rail life, improve ride comfort and reduce noise, etc. Actually when rail grinding plan apply to field track, we should consider a lot of function before determination, such as grinding method, grinding pass number, removing metal volume, etc. because each track has various characteristics. Therefore it is important that the determination of rail grinding strategy for optimum and economic before enforcement.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.10 no.S_3
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• pp.97-106
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• 2001

To improve the water quality, particularly for sea bathers, the behaviour of wastewater from sewage outfalls in water adjacent to Swansea, UK, was studied using a mathematical model. The water quality in the sewage receiving basin was determined using factors like the outfall diffuser location(distance from land boundary), sewage treatment scheme, discharge time, and bacteria decay rate, etc. With respect to these factors, an optimal strategy for sewage discharge was then investigated to minimize bacteria levels along the bathing beaches. As water quality criteria, predicted faecal coliform levels were monitored along the coast adjacent to the outfall locations. The resultant values were compared with EC Mandatory(<2000, 95 % of 20 samples) and Guideline Standards(< 100, 80 % of 20 samples). For the advective-diffusion equation, the non linear advective terms were represented using the ULTIMATE algorithm and the third-order accurate QUICKEST scheme to avoid numerical diffusion. Details of the simulation results are then presented as an optimal policy for sewage discharge in the region.

• International Journal of Concrete Structures and Materials
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• v.11 no.1
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• pp.45-58
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• 2017

Recent investigations have pointed out that current code provisions specifying that the stiffness of reinforced concrete elements is strength independent, and therefore can be estimated prior to any strength assignment, is incorrect. A strength allocation strategy, suitable for preliminary structural design of medium height wall-frame dual systems, is presented for allocating strength in such buildings and estimating the dependable rigidities. The design process may be implemented by either the approximate continuous approach or the stiffness matrix method. It is based on the concept of the inelastic equivalent single-degree-of-freedom system which, the last few years, has been used to implement the performance based seismic design. The aforesaid strategy may also be used to determine structural configurations of minimum rotation distortion. It is shown that when the location of the modal centre of rigidity, as described in author's recent papers, is within a close distance from the mass axis the torsional response is mitigated. The methodology is illustrated in ten story building configurations, whose torsional response is examined under the ground motion of Kobe 1995, component KJM000.

• Smart Structures and Systems
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• v.15 no.3
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.